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Decision Models for the Movie Industry

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Handbook of Marketing Decision Models

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 121))

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Notes

  1. 1.

    In a separate regression equation, Ravid (1999) also considered “return-to-investment” as the dependent variable. The R-square value is low (0.25), and MPAA ratings (G, PG) are the only significant predictors.

  2. 2.

    In a related study, Krider et al. (2005) used a graphical approach to model the lead-lag relationship between distribution and demand for motion pictures. They found that, after the first week, the number of theatres a movie is shown is influenced by its performance in the previous week.

  3. 3.

    In the paper, the author also estimated other specifications that are similar (and some slightly more general) than Equation (13.18). Interested readers are encouraged to see Davis (2006) for more details.

  4. 4.

    We thank Fred Zufryden for this suggestion.

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Author information

Authors and Affiliations

  1. The Wharton School, University of Pennsylvania, Pennsylvania

    Jehoshua Eliashberg

Authors
  1. Jehoshua Eliashberg
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  2. Charles B. Weinberg
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  3. Sam K. Hui
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Corresponding author

Correspondence to Jehoshua Eliashberg .

Editor information

Editors and Affiliations

  1. Erasmus University, Rotterdam, The Netherlands

    Berend Wierenga (Prof) (Prof)

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Eliashberg, J., Weinberg, C.B., Hui, S.K. (2008). Decision Models for the Movie Industry. In: Wierenga, B. (eds) Handbook of Marketing Decision Models. International Series in Operations Research & Management Science, vol 121. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78213-3_13

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